
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "166"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 84 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 80 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.468234	-0.782406	-0.172433	0.727401	-0.162954	-0.874753	0.487138	0.982472	0.7940	0.8015	0.2490	18.018172	16.873148
2459593	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.038132	-1.194800	-0.422793	0.855178	-0.036171	-1.321696	-0.219925	0.360510	0.7266	0.7283	0.2507	5.869490	5.909247
2459592	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.031006	-1.188822	-0.831969	-1.281761	1.167339	-0.079767	1.594320	-0.085607	0.0279	0.0301	0.0014	nan	nan
2459591	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.172846	-1.042043	0.020925	1.066209	0.334407	-1.230326	-0.312980	-0.496002	0.6710	0.6862	0.3657	5.080461	5.039421
2459590	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.178657	-0.664639	0.101577	1.290225	-0.246751	0.108900	0.439506	1.477652	0.6748	0.6848	0.3549	6.067748	5.962458
2459589	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.035422	-0.723153	0.215075	1.161467	0.326624	-0.871023	-0.129165	0.072413	0.7216	0.7199	0.2751	5.710953	5.814770
2459588	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.500740	-0.787333	-0.453750	0.986444	-0.569766	-0.875224	-0.142578	0.182244	0.7653	0.7488	0.2302	10.811051	8.538823
2459587	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	0.497075	-0.852310	0.089911	1.529021	1.771910	1.983481	1.754963	2.213975	nan	nan	nan	7.918154	8.091485
2459586	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.012812	-0.547616	0.606947	0.634542	0.137714	0.840291	-0.734803	0.354175	0.6689	0.6813	0.3429	3.905009	3.762375
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	158.862905	163.000169	inf	inf	30.623615	16.322075	533.805419	1561.421787	nan	nan	nan	0.000000	0.000000
2459584	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.949270	-1.108124	1.020846	0.176948	0.632947	1.024132	-0.684442	-0.363043	0.6176	0.6296	0.3560	1.334866	0.000000
2459583	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.283656	-1.197062	-0.279581	-0.411853	-0.361330	-0.152561	-0.375774	1.023883	0.6761	0.6864	0.3717	2.501413	2.477284
2459582	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.350226	-0.913562	0.052035	-0.463276	0.024133	0.944351	-0.309722	0.692041	0.6805	0.6915	0.3758	4.799165	4.142636
2459581	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.196197	-1.171469	-0.843802	-0.388442	-0.154968	0.484073	-0.191431	0.666790	0.6789	0.6919	0.3757	4.031945	3.847929
2459580	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.296210	-1.032817	0.039461	-0.217523	0.683454	0.099231	-0.637653	0.475713	0.6812	0.6918	0.3711	5.442584	4.951875
2459579	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.030082	-0.914544	0.211723	-0.365256	0.013338	0.911898	0.057662	0.233606	0.6708	0.6819	0.3828	6.410702	6.449677
2459578	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.422665	-0.081748	-0.695757	0.074344	1.884859	-0.805438	-0.442659	-0.646436	0.0323	0.0372	0.0008	nan	nan
2459577	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.907387	-0.927725	-0.676971	-0.534004	-0.176662	0.674070	0.212840	1.275785	0.6767	0.6881	0.3755	5.462315	5.460728
2459576	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.718264	-0.795834	-0.672366	-0.781112	-0.229398	-1.076126	0.856394	1.311188	0.7022	0.7137	0.3711	4.166275	3.981124
2459575	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.686039	-1.066866	-0.481019	-0.707260	-0.874465	-0.456532	-0.683132	-0.740899	0.7664	0.7717	0.3143	4.414364	4.594552
2459574	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.398424	-1.017606	-0.818283	-0.916819	0.427937	-1.490805	-0.784903	-0.239796	0.6966	0.7062	0.3731	4.511757	4.254566
2459573	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.122060	-0.669621	0.207092	-0.120514	-0.016532	0.150715	-0.000783	1.128445	0.6861	0.7053	0.3825	3.483198	3.562029
2459572	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.435923	-1.254360	-0.520529	-0.680604	-0.026050	-0.435477	0.082379	-0.109920	0.6942	0.7126	0.3780	4.503243	4.371754
2459571	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	-0.212097	-0.086837	-0.656886	-0.089758	0.516168	-0.209013	-0.422393	-0.079239	0.0353	0.0395	0.0015	nan	nan
2459570	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.650080	-0.483833	-0.804434	-0.719890	-0.642026	-0.563032	-1.074412	-0.799414	0.6638	0.6911	0.3523	0.000000	0.000000
2459569	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.102867	-1.047101	-0.697038	-0.656125	-0.573669	-0.629284	-0.736253	-0.589670	0.7803	0.7875	0.2228	6.862909	6.483332
2459566	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.914678	-1.135828	-0.342998	-0.348710	-0.341934	-0.619398	-0.655740	0.375733	0.6890	0.7053	0.3879	3.576720	3.346745
2459565	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.025753	-0.847425	0.366280	0.532338	1.250322	1.421491	0.203517	0.550392	0.7025	0.7101	0.3888	3.503922	3.312855
2459563	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.960451	-0.834359	0.525329	1.429465	0.018377	0.262165	0.010999	0.947732	0.6988	0.7102	0.3767	4.184426	3.792476
2459562	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.021518	-1.021438	-0.531242	-0.481065	-0.445685	-0.539358	0.245632	0.190120	0.7041	0.7177	0.3748	2.787103	2.801744
2459561	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.065645	-0.987687	-0.766398	-0.680826	-0.386588	-0.727160	0.169735	0.099549	0.7077	0.7198	0.3722	6.680948	5.590635
2459560	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.844399	-0.979520	-0.522251	-0.670661	-0.053543	-0.623394	0.057156	-0.258943	0.6977	0.7099	0.3887	3.169414	3.172663
2459559	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.157065	-1.287929	-0.657813	-0.719082	-0.517912	-0.866269	-0.003309	-0.179606	0.7020	0.7138	0.3733	3.552151	3.297493
2459558	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.285758	-0.848246	0.257263	-0.215595	-0.114363	-0.037606	-0.252706	0.704281	0.7016	0.7094	0.3872	6.040184	6.102612
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0294	0.0313	0.0008	nan	nan
2459556	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.404758	-1.007450	0.075044	-0.440126	0.196519	-0.548576	-0.607586	-0.580585	0.7007	0.7080	0.3812	6.292286	6.370755
2459554	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7080	0.7184	0.3873	nan	nan
2459553	RF_maintenance	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7068	0.7167	0.3870	nan	nan
2459552	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.336689	-1.087545	-0.027400	0.364662	0.695090	-1.334955	-0.532469	-0.665793	0.7021	0.7176	0.3867	3.896889	4.118847
2459551	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.592348	-0.960875	-0.722942	-0.787050	-0.620935	-0.822029	0.110648	-0.032596	0.6953	0.7157	0.3827	2.967293	3.023242
2459550	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0375	0.0370	0.0002	nan	nan
2459549	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.550530	-0.849597	-0.270183	-0.211119	0.270255	-0.754900	-0.560641	-0.498624	0.6940	0.7128	0.3878	2.905610	3.087603
2459542	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.797740	-1.329826	-0.195887	-0.128160	-0.533048	1.117568	-0.381183	0.353612	0.7635	0.7666	0.3375	6.325673	6.934840
2459541	RF_maintenance	0.00%	1.34%	1.79%	0.00%	100.00%	0.00%	-0.657373	-0.785017	0.029003	-0.315779	-0.447997	-1.287445	-0.977440	-0.787961	0.7555	0.7515	0.3138	9.425188	8.303901
2459540	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.315752	-0.937342	-0.935455	-0.771143	-0.742960	-0.766785	-0.398832	-0.205301	0.7644	0.7633	0.3250	4.411222	4.102126
2459536	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.989271	-0.800549	-0.205096	0.038054	-0.381049	-0.284967	-0.992777	-1.175714	0.7262	0.7325	0.4146	0.000000	0.000000
2459535	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.527684	-0.980015	-0.698099	-0.734627	-1.101681	-0.498639	-0.204922	0.632406	0.7864	0.7781	0.3492	0.813069	0.815803
2459534	RF_maintenance	100.00%	98.66%	98.66%	0.00%	100.00%	0.00%	3.778610	2.518135	-1.580861	-1.781855	2.421679	4.341170	8.360293	8.119951	0.1158	0.1292	0.0431	0.797043	0.797961
2459533	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.564653	-0.685110	0.239617	0.256274	-0.070932	-0.338503	-0.377210	-0.153708	0.7239	0.7295	0.3976	0.000000	0.000000
2459532	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.567594	-1.053252	0.311850	0.078716	0.265319	-0.839677	-0.569856	-0.304330	0.7229	0.7328	0.3966	3.615219	4.175935
2459530	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.544252	-0.892178	-0.597288	-0.616798	-0.298520	-0.463472	-0.304964	-0.190957	0.7394	0.7407	0.3921	0.931596	0.933457
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.286118	-0.668082	-0.155897	0.171568	-0.733038	0.078309	-0.645623	-0.703358	0.9045	0.9365	0.3007	0.000000	0.000000
2459523	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-0.199621	-0.525882	-0.714701	0.119069	1.676605	-0.649985	-0.556697	-0.698435	nan	nan	nan	0.000000	0.000000
2459522	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.546236	0.111913	0.047452	0.110272	2.904692	-0.646352	-0.898059	-0.635090	0.6940	0.7127	0.3007	0.000000	0.000000
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	-0.090824	-0.053571	-0.814810	-0.561145	4.639123	-1.170702	-0.652612	-0.860381	0.0316	0.0402	0.0006	nan	nan
2459508	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.770783	-0.987346	0.028422	-0.295560	0.086326	0.448516	-0.081610	-0.907454	0.9203	0.9595	0.1653	0.000000	0.000000
2459505	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.211725	-1.085094	0.002892	-0.859028	1.173945	-0.818830	-0.259272	-0.049327	0.1183	0.1136	0.0068	1.255280	1.250433
2459503	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.750801	-0.544957	0.552774	0.392510	0.156004	-0.176948	-0.545846	-0.664354	0.8678	0.8719	0.4564	0.000000	0.000000
2459501	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.577808	-0.624850	0.857547	0.718514	-0.250119	-0.184096	-0.855495	-1.064782	0.1867	0.1622	0.0303	0.000000	0.000000
2459500	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.693268	-0.219671	0.530941	0.633538	1.854138	0.988794	-0.938988	-0.870937	0.1821	0.1685	0.0309	0.000000	0.000000
2459499	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.774747	-0.537870	0.508244	0.476525	1.725150	0.940548	-0.271681	0.471170	0.1755	0.1569	0.0191	0.000000	0.000000
2459498	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.496902	-0.373852	0.583909	0.404680	1.539767	0.859857	-0.874991	-0.567347	0.1726	0.1552	0.0333	0.000000	0.000000
2459497	RF_maintenance	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.305277	-0.606352	0.801298	0.562196	2.562432	1.771139	-0.888287	-0.146842	0.2050	0.1678	0.0334	0.000000	0.000000
2459496	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.564863	-0.656195	0.375412	0.378601	2.008420	1.487580	-0.823552	-0.362736	0.9188	0.9336	0.3444	0.000000	0.000000
2459495	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.659843	-0.291844	0.195094	0.412601	1.885436	1.698516	-0.733928	-0.556389	0.9156	0.9288	0.3661	0.000000	0.000000
2459494	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.211332	-0.149982	0.287355	0.482630	2.892754	1.760373	-0.751898	-1.077441	0.9016	0.9182	0.3788	0.000000	0.000000
2459492	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.438350	-0.495064	-0.058381	-0.088767	-0.354817	-0.745699	-0.846175	-1.781706	0.7663	0.8098	0.2953	0.000000	0.000000
2459491	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.102569	-0.296993	-0.377022	-0.611443	0.452813	0.078566	-0.867123	0.156754	0.8037	0.8216	0.2375	0.000000	0.000000
2459490	RF_maintenance	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	6.861227	-0.722930	4.027700	-0.143727	20.294313	1.698007	87.624323	16.702106	0.7295	0.8035	0.3507	0.000000	0.000000
2459489	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.185938	-0.367744	-0.329917	-0.513933	-0.227537	-0.387126	-0.751853	-0.543886	0.7725	0.8118	0.2971	0.000000	0.000000
2459488	RF_maintenance	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.095436	-0.495666	-0.281873	0.191394	0.291966	-0.459265	-1.346032	-1.528949	0.7744	0.8152	0.3227	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 166 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 166, Node 14:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 166: 2459608

Antenna 166: 2459607

Antenna 166: 2459605

Antenna 166: 2459604

Antenna 166: 2459603

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Antenna 166: 2459588

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Antenna 166: 2459583

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Antenna 166: 2459579

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Antenna 166: 2459576

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Antenna 166: 2459570

Antenna 166: 2459569

Antenna 166: 2459566

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Antenna 166: 2459563

Antenna 166: 2459562

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Antenna 166: 2459559

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Antenna 166: 2459556

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Antenna 166: 2459542

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Antenna 166: 2459540

Antenna 166: 2459536

Antenna 166: 2459535

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Antenna 166: 2459532

Antenna 166: 2459530

Antenna 166: 2459527

Antenna 166: 2459524

Antenna 166: 2459523

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Antenna 166: 2459513

Antenna 166: 2459508

Antenna 166: 2459506

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Antenna 166: 2459501

Antenna 166: 2459500

Antenna 166: 2459499

Antenna 166: 2459498

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Antenna 166: 2459496

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶